Bedrock (Page 2)

In: Artificial Intelligence

In recent years, the emergence of large language models (LLMs) has accelerated AI adoption across various industries. However, to further augment LLMs’ capabilities and effectively use up-to-date information and domain-specific knowledge, integration with external data sources is essential. Retrieval Augmented Generation (RAG) has gained attention as an effective approach toContinue Reading

In: Artificial Intelligence

Extracting meaningful insights from unstructured data presents significant challenges for many organizations. Meeting recordings, customer interactions, and interviews contain invaluable business intelligence that remains largely inaccessible due to the prohibitive time and resource costs of manual review. Organizations frequently struggle to efficiently capture and use key information from these interactions,Continue Reading

In: Artificial Intelligence

In the manufacturing world, valuable insights from service reports often remain underutilized in document storage systems. This post explores how Amazon Web Services (AWS) customers can build a solution that automates the digitisation and extraction of crucial information from many reports using generative AI. The solution uses Amazon Nova ProContinue Reading

In: Artificial Intelligence

Generative AI is transforming how businesses deliver personalized experiences across industries, including travel and hospitality. Travel agents are enhancing their services by offering personalized holiday packages, carefully curated for customer’s unique preferences, including accessibility needs, dietary restrictions, and activity interests. Meeting these expectations requires a solution that combines comprehensive travelContinue Reading

In: Artificial Intelligence

Successful generative AI software as a service (SaaS) systems require a balance between service scalability and cost management. This becomes critical when building a multi-tenant generative AI service designed to serve a large, diverse customer base while maintaining rigorous cost controls and comprehensive usage monitoring. Traditional cost management approaches forContinue Reading

In: Artificial Intelligence

Vector embeddings have become essential for modern Retrieval Augmented Generation (RAG) applications, but organizations face significant cost challenges as they scale. As knowledge bases grow and require more granular embeddings, many vector databases that rely on high-performance storage such as SSDs or in-memory solutions become prohibitively expensive. This cost barrierContinue Reading

In: Artificial Intelligence

Amazon Bedrock offers model customization capabilities for customers to tailor versions of foundation models (FMs) to their specific needs through features such as fine-tuning and distillation. Today, we’re announcing the launch of on-demand deployment for customized models ready to be deployed on Amazon Bedrock. On-demand deployment for customized models providesContinue Reading

In: Artificial Intelligence

Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. This enhancement builds on the core functionality of Amazon Bedrock Knowledge Bases , which is designed to seamlesslyContinue Reading